Ultra-marginal Feature Importance: Learning from Data with Causal
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Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees

21 April 2022

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Papers citing "Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees"

19 / 19 papers shown

Title
Manifold Restricted Interventional Shapley Values Muhammad Faaiz Taufiq Patrick Blobaum Lenon Minorics FAtt 102 8 0 10 Jan 2023
SoFaiR: Single Shot Fair Representation Learning Xavier Gitiaux Huzefa Rangwala 56 4 0 26 Apr 2022
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process Christoph Molnar Timo Freiesleben Gunnar Konig Giuseppe Casalicchio Marvin N. Wright B. Bischl 27 61 0 03 Sep 2021
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests Clément Bénard Gérard Biau Sébastien Da Veiga Erwan Scornet FAtt 70 32 0 25 May 2021
A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition Patricia Wollstadt Sebastian Schmitt Michael Wibral 58 30 0 10 May 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 115 302 0 03 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 66 142 0 26 Feb 2021
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 99 250 0 21 Nov 2020
A Weaker Faithfulness Assumption based on Triple Interactions Alexander Marx Arthur Gretton Joris M. Mooij 68 15 0 27 Oct 2020
Bits and Pieces: Understanding Information Decomposition from Part-whole Relationships and Formal Logic A. Gutknecht Michael Wibral Abdullah Makkeh 40 72 0 21 Aug 2020
Causal Feature Selection via Orthogonal Search Ashkan Soleymani Anant Raj Stefan Bauer Bernhard Schölkopf M. Besserve CML 63 17 0 06 Jul 2020
True to the Model or True to the Data? Hugh Chen Joseph D. Janizek Scott M. Lundberg Su-In Lee TDI FAtt 147 166 0 29 Jun 2020
A simple measure of conditional dependence Mona Azadkia S. Chatterjee 151 130 0 27 Oct 2019
A Novel Approach to the Partial Information Decomposition Artemy Kolchinsky 32 55 0 23 Aug 2019
Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance Giles Hooker L. Mentch Siyu Zhou 68 158 0 01 May 2019
Invariant Representations without Adversarial Training Daniel Moyer Shuyang Gao Rob Brekelmans Greg Ver Steeg Aram Galstyan OOD 62 210 0 24 May 2018
Tunability: Importance of Hyperparameters of Machine Learning Algorithms Philipp Probst B. Bischl A. Boulesteix 60 616 0 26 Feb 2018
Privacy with Estimation Guarantees Haobo Wang Lisa Vo Flavio du Pin Calmon Muriel Médard K. Duffy Mayank Varia 63 46 0 02 Oct 2017
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Marvin N. Wright A. Ziegler 267 2,784 0 18 Aug 2015

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